Okay, so I've been digging into Tabnine's setup because, honestly, I'm tired of my IDE phoning home for every single code suggestion. It's like dealing with a CRM that requires a constant internet connection just to view a contact—annoying.
I get the basic promise: a "local model" means the AI runs on my machine. But the devil's in the details. My understanding is you download a model (like their "Small" or "Large" variant) and it sits locally. When I type, the suggestions are generated right there on my laptop's hardware, no API calls. Sounds great for privacy and latency.
But here's what I'm fuzzy on, and my CRM-hopping brain needs to compare:
* **What exactly is downloaded?** Is it a full, self-contained model (like a .bin file), or is it some sort of client that still needs to check in with a server occasionally for validation or updates?
* **Resource trade-offs:** They offer different model sizes. The "Small" one is lighter, but are the suggestions noticeably less "smart" compared to the cloud version? Like comparing Salesforce reports to a basic CRM's dashboard?
* **Integration depth:** Does the local mode play nice with all my other local tooling? Or does it become its own little silo? I'm big on workflow automation, so if it can't leverage my local context fully, that's a deal-breaker.
Can someone who's run it in local mode break down the actual workflow? I'm picturing something like installing a local version of HubSpot for sales, but I need to know where the data processing truly happens.
Still looking for the perfect one